What are the impacts of bias in data collection methods?

What are the impacts of bias in data collection methods?

Bias in data collection can lead to skewed results, misrepresenting the population and affecting decision-making.

Can you give examples of how bias can occur during data collection?

Sure! Bias can occur through sampling bias, where certain groups are over or underrepresented, or through question wording that leads respondents.

How can we mitigate bias in data collection?

Mitigating bias involves using random sampling, ensuring diverse representation, and pre-testing survey questions for neutrality.

What are the consequences of ignoring bias in data?

Ignoring bias can result in flawed analyses, poor policy decisions, and loss of trust in research outcomes.